AGIBOT Unveils GO-3 Preview for Enhanced Robot Learning and Adaptation
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- HumanoidsDaily
AGIBOT co-founder Yao Maoqing introduced the GO-3 Preview at Innovation Day on October 29, showcasing an embodied foundation model aimed at improving robot capabilities through pre-training and real-world experience. The model has achieved top rankings on RoboDojo, RoboTwin, and RoboColiseum, with plans for full open-source release by the end of 2026.
This development is significant as it integrates three systems: GO-3 Preview for general capabilities, Genie Evolver for refining strategies through interaction, and Genie Master for task coordination and experience retention. AGIBOT's approach, termed 'full-lifecycle scaling,' emphasizes continuous learning beyond initial training, enabling robots to adapt their behaviors in various contexts, such as assembly tasks and convenience store operations.
AGIBOT aims to achieve zero-shot task adaptation without specific fine-tuning, leveraging human videos and robot trajectories for training. The company reports successful few-shot adaptation in tasks like LEGO assembly. Genie Evolver utilizes a fleet of 100 robots and physics simulations to enhance learning, allowing insights from one robot's experiences to inform others, thereby fostering collaborative improvement across the fleet.
Original report
AGIBOT GO-3 Preview Links Robot Pre-Training, Practice and Learning on the Job
HumanoidsDaily · [email protected] (Humanoids Daily Staff)This briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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